Triple

T4638532
Position Surface form Disambiguated ID Type / Status
Subject Unna E101592 entity
Predicate hasRailConnectionTo P848 FINISHED
Object Soest E175283 NE FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Soest | Statement: [Unna, hasRailConnectionTo, Soest]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Soest
Context triple: [Unna, hasRailConnectionTo, Soest]
  • A. Soest chosen
    Soest is a historic town in North Rhine-Westphalia, Germany, known for its well-preserved medieval architecture and former significance as a Hanseatic trading center.
  • B. Soest
    Soest is a Dutch town and municipality in the central Netherlands known for its green surroundings and proximity to the Utrechtse Heuvelrug.
  • C. Delmenhorst
    Delmenhorst is a mid-sized industrial and commuter city in northwestern Germany, located near Bremen in the federal state of Lower Saxony.
  • D. Wallhausen
    Wallhausen is a village in present-day Saxony-Anhalt, Germany, historically notable as the birthplace of Otto I, Holy Roman Emperor.
  • E. Hagen
    Hagen is a city in the Ruhr region of North Rhine-Westphalia in western Germany, known historically as an industrial and transport hub.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69bd43d3bc7c81908f81fcf380476b0f completed March 20, 2026, 12:55 p.m.
NER Named-entity recognition batch_69bd5a64214481908a207e8070cc7a45 completed March 20, 2026, 2:32 p.m.
NED1 Entity disambiguation (via context triple) batch_69be103799108190a905c28cdf302aba completed March 21, 2026, 3:27 a.m.
Created at: March 20, 2026, 1:13 p.m.